Provide subject matter expertise throughout the product development cycle and maintain a clear picture of evolving technology development and market trend in AI for medical applications.

Leverage best practices in deep learning / machine learning in the product development cycle for conceptualization, development, integration for medical products and prototypes.

Develop efficient metrics / evaluation criterion to judge algorithmic efficacy and performance, running feasibility studies regarding real-life clinical settings.

Design and develop efficient data curation, annotation, storage and intergration modules for large-scale clinical imaging data sets in a digital ecosystem.      

Foster collaborations with research institutions for potential technology transfer to the AI products team.

Work together with clinical partners to integrate AI products into clinical routine.   Interface with Key Opinion Leaders, product management, and cross-functional and external teams.

Facilitate the integration and deployment of solutions onto cloud platforms / on-premises software services.      

Experience:

 • PhD in Computer Science / Electrical Engineering / Biomedical Engineering / Applied Math with focus on Machine Learning, Image Processing, Computer Vision, Medical Imaging or related domains.

• 2+ years of relevant work experience with solving challenging real-world medical imaging / clinical data science problems.

 

• strong track-record of algorithm development in medical computer vision tasks such as image segmentation, registration, classification and clinical data analysis.

 

• experience in machine learning, preferably deep learning and statistical modelling with knowledge of deep learning frameworks (such as Tensorflow, Caffe, PyTorch, Keras etc.).

 

• excellent software engineering skills and hands-on coding skills with ability to quickly prototype in C++ stand out. Experience in scripting languages such as Python with experience in data science libraries such as NumPy, Scikit-learn, Pandas etc. is a big plus.

 

• experience in software systems architecture, GPU Computing, Web Services and applications and leveraging best software development practices such as productivity toolchains (JIRA, Git etc.)